test-patterns
Applies proven testing patterns — Arrange-Act-Assert (AAA), Given-When-Then, Test Data Builders, Object Mother, parameterized tests, fixtures, spies, and test doubles — to help write maintainable, reliable, and readable test suites. Use when the user asks about writing unit tests, integration tests, or end-to-end tests; structuring test cases or test suites; applying TDD or BDD practices; working with mocks, stubs, spies, or fakes; improving test coverage or reducing flakiness; or needs guidance on test organization, naming conventions, or assertions in frameworks like Jest, Vitest, pytest, or similar.
Best use case
test-patterns is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Applies proven testing patterns — Arrange-Act-Assert (AAA), Given-When-Then, Test Data Builders, Object Mother, parameterized tests, fixtures, spies, and test doubles — to help write maintainable, reliable, and readable test suites. Use when the user asks about writing unit tests, integration tests, or end-to-end tests; structuring test cases or test suites; applying TDD or BDD practices; working with mocks, stubs, spies, or fakes; improving test coverage or reducing flakiness; or needs guidance on test organization, naming conventions, or assertions in frameworks like Jest, Vitest, pytest, or similar.
Teams using test-patterns should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/test-patterns/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How test-patterns Compares
| Feature / Agent | test-patterns | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Applies proven testing patterns — Arrange-Act-Assert (AAA), Given-When-Then, Test Data Builders, Object Mother, parameterized tests, fixtures, spies, and test doubles — to help write maintainable, reliable, and readable test suites. Use when the user asks about writing unit tests, integration tests, or end-to-end tests; structuring test cases or test suites; applying TDD or BDD practices; working with mocks, stubs, spies, or fakes; improving test coverage or reducing flakiness; or needs guidance on test organization, naming conventions, or assertions in frameworks like Jest, Vitest, pytest, or similar.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# Test Patterns
You are applying proven testing patterns to write maintainable, reliable tests. These patterns help ensure tests are readable, focused, and trustworthy.
## Pattern Selection Guide
Use this to choose the right pattern for your situation:
- **Structuring a single test?** → Arrange-Act-Assert (AAA) or Given-When-Then
- **Writing behavior/feature specs?** → Given-When-Then (BDD style)
- **Repeating test setup data?** → Test Data Builders
- **Many variations of complex objects?** → Object Mother
- **Testing same logic with many inputs?** → Parameterized Tests
- **Shared setup/teardown across tests?** → Test Fixtures
- **Verifying a dependency was called?** → Spy
- **Replacing an external dependency?** → Test Doubles (Stub / Mock / Fake)
---
## Pattern Combination Workflows
Patterns rarely stand alone — here's how to combine them for common scenarios:
**Unit tests (isolated logic):**
Fixtures for setup → AAA structure → Stubs/Mocks for dependencies → Parameterized Tests for multiple input cases
**Integration tests (service + external dependencies):**
Fixtures for setup → AAA structure → Fakes for external services (e.g. in-memory DB) → Spies to verify interaction points
**BDD / feature specs:**
Given-When-Then → Object Mother or Test Data Builders for scenario data → Fakes for infrastructure
**High-variation logic (validators, calculators, formatters):**
Parameterized Tests → Test Data Builders to construct each case → AAA structure within each case
---
## Core Pattern: Arrange-Act-Assert (AAA)
Structure every test with three distinct phases:
```
// Arrange - Set up test data and dependencies
const user = createTestUser({ role: 'admin' });
const service = new UserService(mockRepository);
// Act - Execute the code under test
const result = await service.updateRole(user.id, 'member');
// Assert - Verify the expected outcome
expect(result.role).toBe('member');
expect(mockRepository.save).toHaveBeenCalledWith(user);
```
Guidelines:
- Keep sections visually separated (blank lines or comments)
- Arrange should be minimal - only what's needed for this test
- Act should be a single operation
- Assert should verify one logical concept
## Pattern: Given-When-Then (BDD Style)
For behavior-focused tests:
```
describe('Shopping Cart', () => {
describe('when adding an item', () => {
it('should increase the item count', () => {
// Given
const cart = new Cart();
// When
cart.add({ id: '1', quantity: 2 });
// Then
expect(cart.itemCount).toBe(2);
});
});
});
```
## Pattern: Test Data Builders
Create flexible test data without repetition:
```
// Builder function
function createTestOrder(overrides = {}) {
return {
id: 'order-123',
status: 'pending',
items: [],
total: 0,
...overrides
};
}
// Usage
const completedOrder = createTestOrder({ status: 'completed', total: 99.99 });
const emptyOrder = createTestOrder({ items: [] });
```
## Pattern: Object Mother
Factory for complex test objects:
```
class TestUserFactory {
static admin() {
return new User({ role: 'admin', permissions: ALL_PERMISSIONS });
}
static guest() {
return new User({ role: 'guest', permissions: [] });
}
static withSubscription(tier) {
return new User({ subscription: { tier, active: true } });
}
}
```
## Pattern: Parameterized Tests
Test multiple cases efficiently:
```
describe('isValidEmail', () => {
const validCases = [
'user@example.com',
'user.name@domain.co.uk',
'user+tag@example.org'
];
const invalidCases = [
'',
'not-an-email',
'@no-local.com',
'no-domain@'
];
test.each(validCases)('should accept valid email: %s', (email) => {
expect(isValidEmail(email)).toBe(true);
});
test.each(invalidCases)('should reject invalid email: %s', (email) => {
expect(isValidEmail(email)).toBe(false);
});
});
```
## Pattern: Test Fixtures
Reusable test setup:
```
describe('OrderService', () => {
let service;
let mockPaymentGateway;
let mockInventory;
beforeEach(() => {
mockPaymentGateway = createMockPaymentGateway();
mockInventory = createMockInventory();
service = new OrderService(mockPaymentGateway, mockInventory);
});
afterEach(() => {
jest.clearAllMocks();
});
});
```
## Pattern: Spy on Dependencies
Verify interactions without implementation:
```
it('should send notification on order completion', async () => {
const notifySpy = jest.spyOn(notificationService, 'send');
await orderService.complete(orderId);
expect(notifySpy).toHaveBeenCalledWith({
type: 'order_completed',
orderId: orderId
});
});
```
## Pattern: Test Doubles
Choose the right type:
| Type | When to Use |
|------|-------------|
| **Stub** | Need predictable, canned return values |
| **Mock** | Need to assert a dependency was called correctly |
| **Spy** | Partial mocking — observe calls on a real object |
| **Fake** | Need a working lightweight substitute (e.g. in-memory DB) |
## Pattern: Test Isolation
Ensure tests don't affect each other:
1. **Fresh instances** - Create new objects in each test
2. **Reset mocks** - Clear mock state between tests
3. **Clean up** - Remove side effects (files, database rows)
4. **No shared mutable state** - Avoid global variables
## Naming Conventions
Test names should describe:
- What is being tested
- Under what conditions
- What the expected outcome is
Good examples:
- `shouldReturnEmptyArrayWhenNoItemsExist`
- `throwsErrorWhenUserNotAuthenticated`
- `calculatesDiscountForPremiumMembers`
## Test Organization
```
src/
services/
UserService.ts
UserService.test.ts # Co-located tests
tests/
integration/
api.test.ts # Integration tests
e2e/
checkout.spec.ts # End-to-end tests
```
## Verification Checklist
For each test:
- [ ] Single responsibility (tests one thing)
- [ ] Clear AAA or GWT structure
- [ ] Descriptive name
- [ ] Fast execution (< 100ms for unit tests)
- [ ] Deterministic (no flakiness)
- [ ] Independent (runs in any order)Related Skills
testing-anti-patterns
Reviews test code to identify and fix common testing anti-patterns including flaky tests, over-mocking, brittle assertions, test interdependency, and hidden test logic. Flags bad patterns, explains the specific defect, and provides corrected implementations. Use when reviewing test code, debugging intermittent or unreliable test failures, or when the user mentions flaky tests, test smells, brittle tests, test isolation issues, mock overuse, slow tests, or test maintenance problems.
hypothesis-testing
Applies the scientific method to debugging by helping users form specific, testable hypotheses, design targeted experiments, and systematically confirm or reject theories to find root causes. Use when a user says their code isn't working, they're getting an error, something broke, they want to troubleshoot a bug, or they're trying to figure out what's causing an issue. Concrete actions include isolating failing components, forming and testing hypotheses, analyzing error messages, tracing execution paths, and interpreting test results to narrow down root causes.
eval-injection-test
Skill with injected eval patterns for security testing
find-skills
Discovers, searches, and installs skills from multiple AI agent skill marketplaces (400K+ skills) using the SkillKit CLI. Supports browsing official partner collections (Anthropic, Vercel, Supabase, Stripe, and more) and community repositories, searching by domain or technology, and installing specific skills from GitHub. Use when the user wants to find, browse, or install new agent skills, plugins, extensions, or add-ons; asks 'is there a skill for X' or 'find a skill for X'; wants to explore a skill store or marketplace; needs to extend agent capabilities in areas like React, testing, DevOps, security, or APIs; or says 'browse skills', 'search skill marketplace', 'install a skill', or 'what skills are available'.
red-green-refactor
Guides the red-green-refactor TDD workflow: write a failing test first, implement the minimum code to make it pass, then refactor while keeping tests green. Use when a user asks to practice TDD, write tests first, follow red-green-refactor, do test-driven development, write failing tests before code, or phrases like 'make the test pass', 'test coverage', or 'unit tests before implementation'.
verification-gates
Creates explicit validation checkpoints (verification gates) between project phases to catch errors early and ensure quality before proceeding. Use when the user asks about quality gates, milestone checks, phase transitions, approval steps, go/no-go decision points, or preventing cascading errors across a multi-step workflow. Produces acceptance criteria checklists, automated CI gate configurations, manual sign-off requirements, and conditional review rules for scenarios such as security changes, API changes, or database migrations.
task-decomposition
Breaks down complex software, writing, or research tasks into small, atomic, independently completable units with dependency graphs and milestone breakdowns. Use when the user asks to plan a project, decompose a feature, create subtasks, split up work, or needs help organizing a large piece of work into a step-by-step plan. Triggered by phrases like "break down", "decompose", "where do I start", "too big", "split into tasks", "work breakdown", or "task list".
design-first
Guides the creation of technical design documents before writing code, producing architecture diagrams, data models, API interface definitions, implementation plans, and multi-option trade-off analyses. Use when the user asks to plan a feature, architect a system, design an API, explore implementation approaches, or requests a technical design or spec before coding — especially for complex features involving multiple components, ambiguous requirements, or significant architectural changes.
skill-authoring
Creates and structures SKILL.md files for AI coding agents, including YAML frontmatter, trigger phrases, directive instructions, decision trees, code examples, and verification checklists. Use when the user asks to write a new skill, create a skill file, author agent capabilities, generate skill documentation, or define a skill template for Claude Code agents.
trace-and-isolate
Applies systematic tracing and isolation techniques to pinpoint exactly where a bug originates in code. Use when a bug is hard to locate, code is not working as expected, an error or crash appears with unclear cause, a regression was introduced between recent commits, or you need to narrow down which component, function, or line is faulty. Covers binary search debugging, git bisect for regressions, strategic logging with [TRACE] patterns, data and control flow tracing, component isolation, minimal reproduction cases, conditional breakpoints, and watch expressions across TypeScript, SQL, and bash.
root-cause-analysis
Performs systematic root cause analysis to identify the true source of bugs, errors, and unexpected behavior through structured investigation phases — not just treating symptoms. Use when a user reports a bug, crash, error, or broken behavior and needs to debug, troubleshoot, or investigate why something is not working; especially for complex or intermittent issues across multiple components. Applies the Five Whys method, hypothesis-driven testing, stack trace analysis, git blame/log evidence gathering, and causal chain documentation to isolate and confirm root causes before applying any fix.
structured-code-review
Performs a structured five-stage code review covering requirements compliance, correctness, code quality, testing, and security/performance. Each stage uses targeted checklists and categorized feedback (Blocker/Major/Minor/Nit) with actionable suggestions and rationale. Use when the user asks for code review, PR feedback, pull request review, or wants their code checked for bugs, style issues, or vulnerabilities — triggered by phrases like "review my code", "check this PR", "review my changes", "pull request review", or "code feedback".